Consider an IT organisation . There are two units in the organisation- Application Development and Management Team and IT Operation Team . There exist two separate channels for the customers to communicate the organisation- one between the client and application development team for product creation and alteration and the other channel for the customer to communicate the IT operation team for operational issues . Are there any problems with this model ? If you want to set up the IT organisation according to ITIL how you will redesign the communication channels ?
In: Computer Science
Using the following data, perform a oneway analysis of variance
using α=.05. Write
up the results in APA format.
[Group1: 51, 45, 33, 45, 67]
[Group2: 23, 43, 23, 43, 45]
[Group3: 56, 76, 74, 87, 56]
In: Statistics and Probability
For the following reaction Kc = 2.20 ✕ 102 at 74°C. CO(g) + Cl2(g) ↔ COCl2(g) Find the equilibrium concentrations of all chemical species starting with [CO] = 0.105 M and [Cl2] = 0.105 M.
[CO] = M
[Cl2] = M
[COCl2] = M
In: Chemistry
For the following reaction Kc = 2.20 ✕ 102
at 74°C.
CO(g) + Cl2(g) ↔
COCl2(g)
Find the equilibrium concentrations of all chemical species
starting with [CO] = 0.179 M and [Cl2] = 0.287 M.
[CO] = M
[Cl2] = M
[COCl2] = M
In: Chemistry
Find the measures of center for following. Data Frequency 30 - 34 11 35 - 39 18 40 - 44 13 45 - 49 9 50 - 54 8 55 - 59 5 60 - 64 3 65 - 69 0 70 - 74 2
In: Statistics and Probability
REGRESSION. The length of a species of fish is to be represented as a function of the age (measured in days) and water temperature (degrees Celsius). The fish are kept in tanks at 25, 27, 29 and 31 degrees Celsius. After birth, a test specimen is chosen at random every 14 days and its length measured. The dataset is presented below. What is the estimated regression equation?
|
Age |
Temp |
Length |
|
|
1 |
14 |
25 |
620 |
|
2 |
28 |
25 |
1,315 |
|
3 |
41 |
25 |
2,120 |
|
4 |
55 |
25 |
2,600 |
|
5 |
69 |
25 |
3,110 |
|
6 |
83 |
25 |
3,535 |
|
7 |
97 |
25 |
3,935 |
|
8 |
111 |
25 |
4,465 |
|
9 |
125 |
25 |
4,530 |
|
10 |
139 |
25 |
4,570 |
|
11 |
153 |
25 |
4,600 |
|
12 |
14 |
27 |
625 |
|
13 |
28 |
27 |
1,215 |
|
14 |
41 |
27 |
2,110 |
|
15 |
55 |
27 |
2,805 |
|
16 |
69 |
27 |
3,255 |
|
17 |
83 |
27 |
4,015 |
|
18 |
97 |
27 |
4,315 |
|
19 |
111 |
27 |
4,495 |
|
20 |
125 |
27 |
4,535 |
|
21 |
139 |
27 |
4,600 |
|
22 |
153 |
27 |
4,600 |
|
23 |
14 |
29 |
590 |
|
24 |
28 |
29 |
1,305 |
|
25 |
41 |
29 |
2,140 |
|
26 |
55 |
29 |
2,890 |
|
27 |
69 |
29 |
3,920 |
|
28 |
83 |
29 |
3,920 |
|
29 |
97 |
29 |
4,515 |
|
30 |
111 |
29 |
4,520 |
|
31 |
125 |
29 |
4,525 |
|
32 |
139 |
29 |
4,565 |
|
33 |
153 |
29 |
4,566 |
|
34 |
14 |
31 |
590 |
|
35 |
28 |
31 |
1,205 |
|
36 |
41 |
31 |
1,915 |
|
37 |
55 |
31 |
2,140 |
|
38 |
69 |
31 |
2,710 |
|
39 |
83 |
31 |
3,020 |
|
40 |
97 |
31 |
3,030 |
|
41 |
111 |
31 |
3,040 |
|
42 |
125 |
31 |
3,180 |
|
43 |
139 |
31 |
3,257 |
|
44 |
153 |
31 |
3,214 |
|
Y = B0 + B1X1 + B2X2 + e |
||
|
E(Y) = B0 + B1X1 + B2X2 |
||
|
Y-hat = 3904.27 + 26.24X1 - 106.414X2 |
||
|
None of the above |
Part 2
1. REGRESSION. Which variable is the response variable?
|
Age |
||
|
Water temperature |
||
|
Length of fish * |
||
|
Not defined |
Part 3
1. REGRESSION. Is there evidence of collinearity between the independent variables?
|
Yes, temperature and length are collinear in that their correlation is quite high |
||
|
Yes, temperature and age of fish are collinear |
||
|
No, temperature and age have no correlation |
||
|
No, temperature and length have a low correlation |
||
|
Yes, Age and length have a high correlation |
||
|
None of the above |
Part 4
1. REGRESSION. What proportion of the variation in the response variable is explained by the regression?
|
About 90 percent |
||
|
About 81 percent |
||
|
About 85 percent |
||
|
None of the above |
Part 5
1. REGRESSION. The F statistic indicates that:
|
The regression, as a whole, is statistically significant |
||
|
More than half of the variation in Y is explained by the regression |
||
|
Age of fish is an important explanatory variable in the model |
||
|
Length of fish is an important explanatory variable in the model |
||
|
Water temperature is an important explanatory variable in the model |
||
|
None of the above |
Part 6
1. REGRESSION. The t-test of significance indicates that:
|
The regression, as a whole, is statistically significant |
||
|
More than half of the variation in Y is explained by the regression |
||
|
Age of fish contributes information in the prediction of length of fish |
||
|
Length of fish contributes information in the prediction of age of fish |
||
|
Length of fish contributes information in the prediction of temperature |
Part 7
1. REGRESSION. The t-test of significance indicates that (same question but choose the correct answer):
|
The regression, as a whole, is statistically significant |
||
|
More than half of the variation in Y is explained by the regression |
||
|
Length of fish is an important explanatory variable in the model |
||
|
Water temperature is an important explanatory variable in the model |
||
|
None of the above |
Part 8
1. REGRESSION. Assuming you ran the regression correctly, plot the residuals (against Y-hat). The plot shows that:
|
The residuals appear to curve downwards, like a bowl facing down |
||
|
The residuals appear to curve upwards, like a bowl facing up (V shape) |
||
|
The residuals appear to be fanning out and are mostly spread out at the end |
||
|
The residuals appear random |
||
|
None of the above |
Part 9
1. REGRESSION. Which of the following types of transformation may be appropriate given the shape of the residual plot?
|
Logarithmic transformation in both Y and the X variables |
||
|
Quadratic transformation to correct for curvilinear relationship |
||
|
No transformation is necessary |
Part 10
1. REGRESSION. This type of dataset is best described as a ____ and a residual problem common with this type of data is ___
|
Cross-sectional data; heteroscedasticity |
||
|
Time series data; heteroscedasticity |
||
|
Cross-sectional data; residual correlation |
||
|
Time series data; residual correlation |
||
|
Cross-sectional data; multicollinearity |
||
|
None of the above |
In: Statistics and Probability
Throughout the financial year (FY) 2008/2009, world markets experienced the depths of the global financial crisis (GFC). The collapse of the US investment bank Bear Sterns in March 2008 precipitated a rout on those markets that saw the Dow Jones Industrial Average Index drop from over 14,000 points in October 2007 to less than 7,000 points by March 2009. The resulting global contraction in economic growth created challenging operating conditions for Australian companies. Among the decisions confronting financial officers was that of what to do about dividend policy: should dividends be cut to match declines in earnings or should they be maintained at existing levels, resulting in an increase in their dividend payout ratio?
Table 1 below provides data on the earnings and dividend payments of four selected Australian Securities Exchange (ASX) listed companies for the period surrounding the GFC. The companies are: Australia &New Zealand Banking Group Ltd (ANZ), Westpac Banking Corporation Limited (WBC), Suncorp Group Ltd (SUN) and Downer EDI Ltd (DOW). The data in the table was sourced from individual company statements.
As we can see from the table (in which figures of particular interest are shown in bold type), the dividend payout ratios of all of the companies increased around the time of the GFC. For example, ANZ paid out the same total dividend ($1.36) in the financial year ended June 2008 as it did the previous year, despite the 28%decline in its earnings per share (EPS) from $2.048 in the financial year 2006/2007 to $1.478 in the financial year 2007/2008. This resulted in the company’s payout ratio increasing from the typical figure of around 60–5% of earnings in other years to 92% of earnings in financial year 2007/2008. Westpac was able to increase both its earnings and its dividends in the first year of the financial crisis but was forced to slash dividends and increase its payout ratio in the financial year 2008/2009 as the crisis began to bite. Likewise, both Suncorp and Downer EDI increased their payout ratios above ‘normal’ levels during the financial years 2007/2008 and 2008/2009.
These figures illustrate the difficulties that financial managers face in setting dividend policy, particularly during an unprecedented crisis such as the one that occurred between 2007 and 2009.
Table 1: Dividend payout ratios for selected Australian companies between the financial years (FY) 2005/2006 and 2009/2010
|
ASX code |
Data |
Financial Years |
||||||||
|
2005/2006 |
2006/2007 |
2007/2008 |
2008/2009 |
2009/2010 |
||||||
|
ANZ DPS (cps) |
||||||||||
|
-Interim |
56.00 |
62.00 |
62.00 |
46.00 |
52.00 |
|||||
|
-Final |
69.00 |
74.00 |
74.00 |
56.00 |
74.00 |
|||||
|
-Special |
0.00 |
0.00 |
0.00 |
0.00 |
0.00 |
|||||
|
-Total DPS |
125.00 |
136.00 |
136.00 |
102.00 |
126.00 |
|||||
|
EPS (cps) |
188.65 |
204.81 |
147.83 |
166.52 |
195.00 |
|||||
|
Payout Ratio (%) |
66.26 |
66.40 |
92.00 |
61.25 |
64.62 |
|||||
|
WBC DPS ($) |
||||||||||
|
-Interim |
56.00 |
63.00 |
70.00 |
56.00 |
65.00 |
|||||
|
-Final |
60.00 |
68.00 |
72.00 |
60.00 |
74.00 |
|||||
|
-Special |
0.00 |
0.00 |
0.00 |
0.00 |
0.00 |
|||||
|
-Total DPS |
116.00 |
131.00 |
142.00 |
116.00 |
139.00 |
|||||
|
EPS (cps) |
163.66 |
183.02 |
194.31 |
121.68 |
189.50 |
|||||
|
Payout Ratio (%) |
70.01 |
70.70 |
72.18 |
94.16 |
72.45 |
|||||
|
SUN DPS (cps) |
||||||||||
|
-Interim |
47.00 |
52.00 |
52.00 |
20.00 |
15.00 |
|||||
|
-Final |
50.00 |
55.00 |
55.00 |
20.00 |
20.00 |
|||||
|
-Special |
0.00 |
0.00 |
0.00 |
0.00 |
0.00 |
|||||
|
-Total DPS |
97.00 |
107.00 |
107.00 |
40.00 |
35.00 |
|||||
|
EPS (cps) |
157.10 |
149.59 |
56.39 |
31.11 |
64.39 |
|||||
|
Payout Ratio (%) |
58.24 |
67.47 |
178.97 |
128.58 |
54.36 |
|||||
|
DOW DPS (cps) |
||||||||||
|
-Interim |
12.00 |
13.00 |
13.00 |
13.00 |
13.10 |
|||||
|
-Final |
8.00 |
8.00 |
12.50 |
16.00 |
16.00 |
|||||
|
-Special |
0.00 |
0.00 |
0.00 |
0.00 |
0.00 |
|||||
|
Total DPS |
20.00 |
21.00 |
25.50 |
29.00 |
29.10 |
|||||
|
EPS (cps) |
44.67 |
49.25 |
45.88 |
50.90 |
57.10 |
|||||
|
Payout Ratio (%) |
43.24 |
41.18 |
53.68 |
55.03 |
49.22 |
|||||
(a) DPS denotes dividends per share
(b) EPS denotes earnings per share
(c) cps denotes cents per share.
Requirement 1:
An examination of the payout ratios of Suncorp Group Ltd in financial years 2007/2008 and 2008/2009 finds them to be above 100%. Why would the organisation pay out more as a dividend than it generates in earnings?
Requirement 2:
Why might Downer EDI have chosen to increase its dividend payment in FY2007/2008, even though its earnings per share declined in that year?
In: Finance
The fill amount of bottles of a soft drink is normally distributed, with a mean of 2.0 liters and a standard deviation of 0.04 liter. Suppose you select a random sample of 25 bottles.
a. What is the probability that the sample mean will be between 1.99 and 2.0 liters ?
b. What is the probability that the sample mean will be below 1.98 liters ?
c. What is the probability that the sample mean will be greater than 2.01 liters?
d. The probability is 99 % that the sample mean amount of soft drink will be at least how much?
e. The probability is 99 % that the sample mean amount of soft drink will be between which two values (symmetrically distributed around the mean)?
a. The probability is ____ (Round to three decimal places as needed.)
b.The probability is ____. (Round to three decimal places as needed.)
c. The probability is____. (Round to three decimal places as needed.)
d. There is a 99 % probability that the sample mean amount of soft drink will be at least ____liter(s). (Round to three decimal places as needed.)
e. There is a 99 % probability that the sample mean amount of soft drink will be between ____liter(s) and nothing liter(s). (Round to three decimal places as needed. Use ascending order.)
In: Statistics and Probability
Prepare Journal Entries for the following transactions:
| Byte of Accounting, Inc. | |
| Transaction | Description of transaction |
| 21. | June 28: Billed $5,490 to miscellaneous customers for services performed to June 25. |
| 22. | June 29: Cash in the amount of $5,201 was received for billings. |
| 23. | June 29: Paid the bill received on June 22, from Computer Parts and Repairs Co. |
| 24. | June 29: Paid salaries of $1,035 to equipment operators for the week ending June 25. |
| 25. | June 30: Received a bill for the amount of $940 from O & G Oil and Gas Co. |
| 26. | June 30: Paid a cash dividend of $0.17 per share to the three shareholders of Byte. [IMPORTANT NOTE: The number of shares of capital stock outstanding can be determined from the first three transactions.] |
| Adjusting Entries - Round to two decimal places. | |
| 27. | The rent payment made on June 17 was for June, July and August. Expense the amount associated with one month's rent. |
| 28. | A physical inventory showed that only $236.00 worth of office supplies remained on hand as of June 30. |
| 29. | The annual interest rate on the mortgage payable was 7.50 percent. Interest expense for one-half month should be computed because the building and land were purchased and the liability incurred on June 16. |
| 30. | Information relating to the prepaid insurance may be obtained from the transaction recorded on June 14. Expense the amount associated with one half month's insurance. |
| 31. | A review of Byte’s job worksheets show that there are unbilled revenues in the amount of $5,000 for the period of June 28-30. |
| 32. | The fixed assets have estimated useful lives as follows: |
| Building - 31.5 years | |
| Computer Equipment - 5.0 years | |
| Office Equipment - 7.0 years | |
| Use the straight-line method of depreciation. Management has decided that assets purchased during a month are treated as if purchased on the first day of the month. The building’s scrap value is $8,500. The office equipment has a scrap value of $500. The computer equipment has no scrap value. Calculate the depreciation for one month. | |
| 33. | A review of the payroll records show that unpaid salaries in the amount of $621 are owed by Byte for three days, June 28 - 30. |
| 34. | The note payable relating to the June 2, and 10 transactions is a five-year note, with interest at the rate of 12 percent annually. Interest expense should be computed based on a 360 day year. |
| [IMPORTANT NOTE: The original note on the computer equipment purchased on June 2 was $120,000. On June 10, eight days later, $23,000 was repaid. Interest expense must be | |
| calculated on the $120,000 for eight days. In addition, interest expense on the $97,000 balance of the loan ($120,000 less $23,000 = $97,000) must be calculated for the 20 days remaining in the month of June.] | |
| 35. | Income taxes are to be computed at the rate of 25 percent of net income before taxes. |
| [IMPORTANT NOTE: Since the income taxes are a percent of the net income you will want to prepare the Income Statements through the Net Income Before Tax line. The worksheet contains all of the accounts and their balances which you can then transfer to the appropriate financial statement.] | |
| Closing Entries | |
| 36. | Close the revenue accounts. |
| 37. | Close the expense accounts. |
| 38. | Close the income summary account. |
| 39. | Close the dividends account. |
In: Accounting
Explain three ways of memory compaction.
Demonstrate three types of scheduling by process manager with the help of diagram(s).
List differences between hosted and bare metal virtualization. Also, provide one example of each.
In: Computer Science